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Hi All

i have downloaded following code from web that inputs sound samples and displays spectrum, i want to print frequencies present in each second in the spectrum.i.e

when ever the spectrum is displayed i want to print those frequencies as well on the console. Below is the code i am using i initially used "print fftx". Is "fftx" present in the code is frequency. Also how can i measure the amplitude of each frequency so as next step i will print three frequencies with the top most amplitude.

Thanks in advance.

```
import pyaudio
import scipy
import struct
import scipy.fftpack
from Tkinter import *
import threading
import time, datetime
import wckgraph
import math
#ADJUST THIS TO CHANGE SPEED/SIZE OF FFT
bufferSize=2**11
#bufferSize=2**8
# ADJUST THIS TO CHANGE SPEED/SIZE OF FFT
sampleRate=48100
#sampleRate=64000
p = pyaudio.PyAudio()
chunks=[]
ffts=[]
def stream():
global chunks, inStream, bufferSize
while True:
chunks.append(inStream.read(bufferSize))
def record():
global w, inStream, p, bufferSize
inStream = p.open(format=pyaudio.paInt16,channels=1,\
rate=sampleRate,input=True,frames_per_buffer=bufferSize)
threading.Thread(target=stream).start()
def downSample(fftx,ffty,degree=10):
x,y=[],[]
for i in range(len(ffty)/degree-1):
x.append(fftx[i*degree+degree/2])
y.append(sum(ffty[i*degreei+1)*degree])/degree)
return [x,y]
def smoothWindow(fftx,ffty,degree=10):
lx,ly=fftx[degree:-degree],[]
for i in range(degree,len(ffty)-degree):
ly.append(sum(ffty[i-degree:i+degree]))
return [lx,ly]
def smoothMemory(ffty,degree=3):
global ffts
ffts = ffts+[ffty]
if len(ffts) <= degree:
return ffty
ffts=ffts[1:]
return scipy.average(scipy.array(ffts),0)
def detrend(fftx,ffty,degree=10):
lx,ly=fftx[degree:-degree],[]
for i in range(degree,len(ffty)-degree):
ly.append(ffty[i]-sum(ffty[i-degree:i+degree])/(degree*2))
#ly.append(fft[i]-(ffty[i-degree]+ffty[i+degree])/2)
return [lx,ly]
def graph():
global chunks, bufferSize, fftx,ffty, w
if len(chunks)>0:
data = chunks.pop(0)
data=scipy.array(struct.unpack("%dB"%(bufferSize*2),data))
#print "RECORDED",len(data)/float(sampleRate),"SEC"
ffty=scipy.fftpack.fft(data)
fftx=scipy.fftpack.rfftfreq(bufferSize*2, 1.0/sampleRate)
fftx=fftx[0:len(fftx)/4]
ffty=abs(ffty[0:len(ffty)/2])/1000
ffty1=ffty[:len(ffty)/2]
ffty2=ffty[len(ffty)/2::]+2
ffty2=ffty2[::-1]
ffty=ffty1+ffty2
ffty=scipy.log(ffty)-2
#fftx,ffty=downSample(fftx,ffty,5)
#fftx,ffty=detrend(fftx,ffty,30)
#fftx,ffty=smoothWindow(fftx,ffty,10)
ffty=smoothMemory(ffty,3)
#fftx,ffty=detrend(fftx,ffty,10)
w.clear()
#w.add(wckgraph.Axes(extent=(0, -1, fftx[-1], 3)))
w.add(wckgraph.Axes(extent=(0, -1, 6000, 3)))
w.add(wckgraph.LineGraph([fftx,ffty]))
w.update()
if len(chunks)>20:
print "falling behind...",len(chunks)
def go(x=None):
global w,fftx,ffty
print "STARTING!"
threading.Thread(target=record).start()
while True:
graph()
root = Tk()
root.title("SPECTRUM ANALYZER")
root.geometry('500x200')
w = wckgraph.GraphWidget(root)
w.pack(fill=BOTH, expand=1)
go()
mainloop()
```